1. Field
The embodiments discussed herein are directed to a user state presumption system, a user state presumption method, and a computer-readable recording medium storing a user state presumption program causing a computer to presume the state of a user on the basis of data indicating access histories of a plurality of users whose computers have accessed a server.
2. Description of the Related Art
For example, behaviors of website users differ from individual to individual. However, in a case where website users are grouped into category groups of users having common characteristics, users belonging to the same category group may exhibit a common behavior pattern. For example, in the case that “a degree of interest in a website”, which degree is one of user characteristics, is measured, the following tendencies can be founds users in a category group of users with a high degree of interest tend to stay at the website for a long time, whereas users in a category group of users with a low degree of interest tend to stay at the website for a short time.
For example, in the case that the characteristics of an individual user of a website providing a product sales service are acquired, an operator of the website is able to carry out measures, such as changing of a page to be displayed on the basis of the characteristics of the user. Thus, the operator can increase the probability that the user will purchase a product or the degree that the users will be satisfied. Even in a case where the characteristics of an individual user cannot be specified, if the proportion of users who have certain characteristics among all users can be presumed, the operator of the website is able to carry out measures, such as changing of an advertisement to be displayed, so as to increase both the probability that the users will purchase products and the degree that the users will be satisfied.
When the above-mentioned website providing a product sales service is compared with in-person retail sales in stores, the presuming the characteristics of a website user corresponds to the way in which a resourceful salesperson in a store sells. The resourceful salesperson understands both preferences and desires of a customer through conversation with the customer and properly guides a customer to a desired product. In addition, presuming the characteristics of a website user group corresponds to the way in which a salesperson in a store. The resourceful salesperson understands both strong points and weak points of a product for sale, with which competing products are likely to be compared, and rise and decline of fads, and the like through conversation with many customers. Accordingly, obtained information, by presuming the characteristics of the website user group, can be properly fed back to production and sales plans for products.
For example, in a case where a campaign for a particular product is carried out on a website, it is important to understand user characteristics such as the degree of interest in the product, the degree of comprehension of the product, and the intention of purchasing the product, to judge measures to acquire users in the campaign. In the case that the user characteristics include both a low degree of comprehension and a low degree of interest, measures for strengthening advertising to increase name recognition are effective. On the other hand, in the case that the user characteristics includes a degree of comprehension of the product is high but a degree of interest is low, measures, such as price reduction, are effective.
The above-described user characteristics, such as the degree of interest and the degree of comprehension, can be presumed on the basis of questionnaire surveys Conventionally, in a model, before purchasing a product, a consumer goes through intermediate stages, such as “attention”, “brand comprehension”, “attitude”, “intention”, and the like, and such consumer states “can be measured on the basis of consumer surveys, such as questionnaires”.
Conventionally, acquiring characteristics of website users, such as preferences and interests, and distributing advertisements corresponding to the characteristics of the website users, a technique such as behavioral targeting advertisement (abbreviated as “BTA”) has been available.
Behavioral targeting advertisement may be defined as a “new marketing procedure for grouping users into segments on the basis of behavioral history information on a website and distributing optimal advertisements according to the segments”.
In addition, conventionally, the BTA server described below is discussed as an example of behavioral targeting advertisement. That is, on the basis of both user IDs of website users and information on URLs of web pages referred to by the website users, the BTA server allocates a segment ID for a particular area to a user ID of a user who frequently browses web pages in the particular area, such as automobiles or cosmetics. The BTA server includes a database for controlling which segment IDs are to be allocated to individual user IDs. Accordingly, advertisements corresponding to segment IDs can be distributed to users who have segment IDs responding user IDs.
Measures that can be taken by understanding behaviors of users are not only applied to distribution of advertisements. Thus, in this specification, a general technique for grouping users into segments on the basis of behavioral history information of the users will be referred to as a behavioral targeting technique, without being limited to an advertising application. As a behavioral targeting technique, for example, a system for providing information, a product, and a service suitable for a user on the basis of a user behavior, such as the number of times the user has visited a particular homepage, and user information, such as the age of the user, has been discussed.
However, as described above, it is difficult to perceive how characteristics of a user change on the basis of a behavior of the user for browsing information. The characteristics of a user may change depending on browsing of information on a website or interaction with the website.
A case where a commission discount campaign is available for foreign currency deposits on a bank's website will be discussed as an example of a change in characteristics of a user. In the case of purchasing a high-risk service, such as a foreign currency deposit, even if a discount campaign is available, users cannot casually purchase the service. A certain level of decision-making is necessary for users to purchase such a service. For a campaign for such a service, a plurality of explanatory pages for explaining characteristics and risks of purchasing the service exist on a website. Thus, it is assumed that many users carefully browse such explanatory pages to help their decision-making.
After a user has carefully browsed such explanatory pages, user characteristics, such as the degree of interest in the service and the intention of purchasing the service, change. For example, as a result of browsing of such explanatory pages, some users come to fully comprehend the service and their intention of purchasing the service is increased, whereas some users come to lose their interest in the service after comprehending the service.
In the BTA described conventionally, for example, users who frequently browsed web pages of a particular area are grouped into a segment of users who have a high degree of interest in the particular area. Thus, the users in the segment of users who have a high degree of interest become targets for advertising of the particular area. However, some users belonging to the segment of users who have a high degree of interest may have judged that products in the particular area are not worth purchasing after browsing the web pages of the particular area. That is, it is difficult to understand how the characteristics of a user who frequently browses the web pages of the particular area change.